22 citations · 82 across the 10 of their papers we have counts for
4 papers · 1 filter
SPLICE: A Synthetic Paid Loss and Incurred Cost Experience Simulator
Benjamin Avanzi, Gregory Clive Taylor, Melantha Wang
In this paper, we first introduce a simulator of cases estimates of incurred losses, called `SPLICE` (Synthetic Paid Loss and Incurred Cost Experience). In three modules, case esti…
SynthETIC: an individual insurance claim simulator with feature control
Benjamin Avanzi, Gregory Clive Taylor, Melantha Wang +1
Recent years have seen rapid increase in the application of machine learning to insurance loss reserving. They yield most value when applied to large data sets, such as individual…
On the modelling of multivariate counts with Cox processes and dependent shot noise intensities
Benjamin Avanzi, Gregory Clive Taylor, Bernard Wong +1
In this paper, we develop a method to model and estimate several, _dependent_ count processes, using granular data. Specifically, we develop a multivariate Cox process with shot no…
Modelling and understanding count processes through a Markov-modulated non-homogeneous Poisson process framework
Benjamin Avanzi, Greg Taylor, Bernard Wong +1
The Markov-modulated Poisson process is utilised for count modelling in a variety of areas such as queueing, reliability, network and insurance claims analysis. In this paper, we e…